Supporting Online Material for:
Charts and Demand: Empirical Generalizations on Social Influence
1. Experimental Design
Following Salganik, Dodds, and Watts (2006) (SDW), we employed a social macro
experiment consisting of two experimental conditions into which respondents were randomly
assigned with twice as many respondents in the independent than in the social influence
condition. In both groups, respondents were consecutively confronted with three product
categories (music, movies, and scarves) with 30 products each, where they (1) could listen to
and download music songs, (2) indicated which movies they would be interested in, and (3)
indicated which scarves they would consider. Participants could also rate products on a five
star scale, which is widely used in an online context, e.g., in online stores such as amazon.
In the independent condition, respondents could listen to the songs (music) or saw a product
picture with a description (movies and scarves). In the social influence condition, respondents
additionally saw the number of downloads/sales by previous participants in real-time (Fig.
A1).
SDW used one independent condition, but replicated the social influence condition eight
times (“worlds”). Participants were recruited via online banners and guided to a music
website where they saw 48 songs in descending order of popularity (social influence
conditions) or randomized (independent condition). On the music website, respondents could
listen to unknown songs. While listening, they saw a pop-up window with a five star rating
scale and a download button where they could rate and indicate their download decision for
every song.
Figure A1: Screenshot of the selection tasks. In the independent condition, no information on
previous downloads was available. Whenever respondents indicated they wanted to download
a song, a file transfer was automatically initiated. For movies/scarves participants simply
indicated whether or not they would be interested in/consider each of the alternatives.
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2. Subject recruitment
1,143 participants were recruited from a commercial online panel in 2012. Women comprised
58.3% of the sample. On average, fewer songs were downloaded than products chosen for
sale (Table A1), which we attribute to the longer time it took to download a song than to click
on a product.
Present study
SDW
Category
Independent
Influence
n
771
372
Downloads songs
(mean)
2.57
Interest movies (mean)
Independent
Influence
1,143
1,446
5,746
7,192
2.77
2.64
1.5
1.4
1.4
7.57
7.26
7.47
-
-
-
Consideration scarves
(mean)
8.89
7.87
8.56
-
-
-
Female (%)
57.7
59.4
58.3
n/a
n/a
73.9
≤17
4.59
6.62
5.24
50.9
18-24
31.80
25.09
29.65
39.2
25-31
26.23
29.62
27.31
32-38
29.02
30.66
29.54
39+
8.36
8.01
8.25
Age (%)
Total
n/a
Total
n/a
9.9
Table A1: Descriptives
3. Product selection
As we were interested in replicating and expanding the results of SDW, we chose music,
movies (as a second cultural market), and scarves (as an identity relevant fashion item) as our
main product categories. To avoid possible noise due to brand labels and price, we erased any
visible labels and selected scarves without brand reference (like the Burberry tartan) from a
similar price category. We also decided to use Bollywood movies to minimize previous
knowledge (Table A2). To make the movies comparable, we erased any indication for release
dates and made use of mainstream genres.
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Movie title
Om Shanti Om
Bollywood/Hollywood
Always Kabhi Kabhi
Love Aaj Kal
Milenge Milenge
Khatta Meetha
Ek Main Aur Ekk Tu
Tere Naal Love Ho Gaya
Jodi Breakers
The Dirty Picture
Tere Mere Phere
Tell Me O Kkhuda
Breakaway
Aarakshan
Bol
Zindagi Na Milegi Dobara
Double Dhamaal
Bbuddah Hoga Terra Baap
Chillar Party
Mausam
Rockstar
Ra One
Udaan
Yamla Pagla Deewana
Dhobi Ghat
Dil Toh Baccha Hai Ji
Toonpur Ka Superrhero
Isi Life Mein...!
Jhootha Hi Sahi
Do Dooni Chaar
Table A2: List of 30 selected Bollywood movies used in the experiment.
The songs used in our study were obtained from a rights-free music website
(http://freemusicarchive.org/) which features largely unknown artists (Table A3). We also
ensured that the selected songs represented mainstream genres.
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Band name
Song name
et_
Children
Lab Coast
Really Realize
Gain
Somos Aire
The Search
The Heart is A Lonely
Gringo Star
Ask me why
Lorenzo's Music
You Got to Feel it Tonight
Learning Music
Night Lights
Meanwhileproject ltd.
That Day Joey Burns
Kodak to Graph
Zolembo
Clinical Archives
Joe Frawley - Meditation
Keshco
Fly by Nights
The Kyoto
Epilogue
Hands
Hold
Steven Smirney
Deeply Wrong Merrits
Garmisch
Glimmer
Belkastrelka
Lirik Untuk Lagu Pop
coverclub nl.
Laura Vane & the
Milk Music
I've got a wild feeling
Ergo Phizmiz
Sticky white Glue Part 7
The Simple
Caitlin's on the Beach
Kellee Maize
Takeover
The Woolen Men
Land of Laughs
Austin Leonard
Glowing Windows
Yacht
Love in the Dark
Decade in Exile
B.L.A. by Decade in Exile
Bandana Splits
Back to School
Chris Elam
Nothing’s there
The Agrarians
Recognize an Hour Divine
Lame Drivers
Other Side
Halloween
Monster on Campus
Rhys Lloyd Morgan
The Morning Sun
Table A3: List of 30 selected songs used in the experiment.
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4. Data analysis
We follow SDW and calculate Gini coefficient to measure market concentration:
(1) Market Share (Fig. A2): 𝑚𝑖 =
𝑑𝑖
∑𝑆
𝑘=1 𝑑𝑘
where 𝑑𝑖 =
Number of choices per product i and S = Total number of products per category
1 𝑆
∑
∑𝑆 |𝑚𝑖 −𝑚𝑗 |
𝑆2 𝑖=1 𝑗=1
∑𝑆
𝑘=1 𝑚𝑘
(2) Gini coefficient: 𝐺 =
2×
where
𝑆
𝑚 = Market share for certain product and S = Total number of songs
We tested the significance between the Gini coefficient of the independent and social
influence worlds by
1. Randomly splitting the independent condition into two groups and calculating the Gini
coefficient for one half, a procedure which we repeated 1,000 times (cf. SDW).
2. Testing whether the difference between each independent Gini coefficient and the social
Rank: minfluence
Music
minfluence
influence Gini coefficient was > 0 which data confirms with p <.001 for all categories.
0.08
0.06
0.04
30
20
10
0.02
0
0
0
0.02
0.04
0.06
0.08
0
10
0.05
0.04
0.03
30
20
0
0.03
0.04
0.05
0
10
mindependent
0.06
0.04
20
30
Rank: mindependent
Rank: minfluence
minfluence
30
10
0.02
0.02
Scarves
20
Rank: mindependent
Rank: minfluence
Movies
minfluenc
mindependent
30
20
10
0.02
0
0.02
0.04
0.06
mindependent
0
10
20
30
Rank: mindependent
Fig. A2: Market shares in independent and social influence markets (n=1,143)
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5. Robustness checks
Our sample size is smaller than that of SDW. However, the data reflects relatively stable Gini
coefficients (cf. Fig. A3).
Figure A3: Dynamics of the Gini coefficients
We also checked whether the actual behavior (download/interest/consideration) mirrors the
self-reported liking (star rating) (cf. SDW). We can see across categories that this is the case
(Fig. A4). Note: Average song downloads are lower than interest in scarves and movies
resulting in lower download likelihoods across all ratings (cf. Table A1).
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Figure A4: Relationship between star ratings and demand, interest and consideration.
References
Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006). Experimental Study of Inequality and
Unpredictability in an Artificial Cultural Market. Science, 311, 854-856.
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